Carotid dual-energy CT angiography: Evaluation of low keV calculated monoenergetic datasets by means of a frequency-split approach for noise reduction at low keV levels. Issue 4 (April 2016) - Riffel, Philipp
Highlights: Introduction of a new monoenergetic imaging algorithm for calculated monoenergetic keV datasets using a frequency-split technique. Noise reduction in ultra-low keV monoenergetic data sets compared to previous monoenergetic reconstruction techniques. Improved image quality of ultra-low keV monoenergetic DECT. Abstract: Background and purpose: Calculated monoenergetic ultra-low keV datasets did not lead to improved contrast-to-noise ratio (CNR) due to the dramatic increase in image noise. The aim of the present study was to evaluate the objective image quality of ultra-low keV monoenergetic images (MEIs) calculated from carotid DECT angiography data with a new monoenergetic imaging algorithm using a frequency-split technique. Materials and methods: 20 patients (12 male; mean age 53 ± 17 years) were retrospectively analyzed. MEIs from 40 to 120 keV were reconstructed using the monoenergetic split frequency approach (MFSA). Additionally MEIs were reconstructed for 40 and 50 keV using a conventional monoenergetic (CM) software application. Signal intensity, noise, signal-to-noise ratio (SNR) and CNR were assessed in the basilar, common, internal carotid arteries. Results: Ultra-low keV MEIs at 40 keV and 50 keV demonstrated highest vessel attenuation, significantly greater than those of the polyenergetic images (PEI) (all p -values <0.05). The highest SNR level and CNR level was found at 40 keV and 50 keV (all p -values <0.05). MEIs with MFSA showed significantly lower noise levels than those processed with CM (all p -values <0.05) and no significant differences in vessel attenuation ( p > 0.05). Thus MEIs with MFSA showed significantly higher SNR and CNR compared to MEIs with CM. Conclusion: Combining the lower spatial frequency stack for contrast at low keV levels with the high spatial frequency stack for noise at high keV levels (frequency-split technique) leads to improved image quality of ultra-low keV monoenergetic DECT datasets when compared to previous monoenergetic reconstruction techniques without the frequency-split technique.